Abstract

This study focuses on a new approach to estimate financial wellbeing indicators for merchants, by looking at behavioral patterns of their customers using transaction history. The transaction data for about 10,000 merchants in a specific country, was analyzed in terms of diversity and propensity of their customers using factors like age, distance travelled to shop, time of the day for shopping, day of the week for shopping, educational status, gender etc. These factors were used as independent variables to predict the financial well-being of merchants, particularly in two dimensions – total revenue and consistency in revenue, both relative to other merchants in the same industry. The merchants were then also divided into the categories of Essential, Non- essential and Luxury goods depending on the industry they belong to and it was interesting to observe the contrast across categories. The results suggest that behavioral patterns could be used to augment current methods of calculating credit score.